Monthly Archives: January 2014

Walking Roller Coaster

I grew up at Kings Island, and I love roller coasters. One of the best rides I ever had was when I was on Drop Zone. The ride went to the top of its climb, and got stuck. There were announcements that we’d be up there awhile while they fixed something. While that freaked a lot of people out, I thought it was awesome because the view was amazing and the weather was great. I was up there long enough to find the neighborhood where my parent’s home was. After 10ish minutes, we could tell that whatever was broken was being fixed. There was a heightened anticipation of “when are we going to drop?” We made it down alive though.

The thing about normal coaster rides is that they don’t stop. So if you want to enjoy the view, you better do it quick. This new “coaster” in Germany doesn’t quite have that problem though. It’s a walking coaster with a loop. I… don’t think you can actually walk the loop, but I’m not positive. I can’t figure out how it would work and no one is on it in any of the pictures. But still, a cool idea with some pretty views that you can watch for as long as desired.

Reds Caravan Reveals Team Employs 3 Programmers

The Reds Caravan rolled through Bloomington yesterday. This edition of the traveling side-show featured Marty Brennaman, Eric Davis, Assistant GM Bob Miller, new guy Brayan Pena, minor leaguer Tucker Barnhart, and Big Red Machine glue-guy Doug Flynn. After Marty introduced everyone, he opened up the floor to questions. I asked Bob Miller about the status of the Reds’ Analytics efforts. He tried to convey the vast amount of data that the team collects, including over 90 data points for every pitch thrown. The Director of Baseball Research/Analysis is Sam Grossman, who heads a team of three programmers. The team also employs over 20 scouts, which are especially necessary for understanding high school and foreign talent where the data on the player’s performance is sparser/non-existant.

While I appreciate the honest and helpful answer from Mr. Miller, I wonder whether having three people doing analytics for a team that is going to spend $100M+ each year on player payroll is enough. Do other teams have more analytics professionals? The Reds, under the Dusty Baker regime, tended to ignore a lot of largely accepted analytics wisdom:
-Baker consistently batted his shortstop in the top 2 spots in the order, despite the Reds not having an above-average bat playing shortstop
-The Reds left Aroldis Chapman, one of the most dominant pitchers in baseball, to languish in the closer roll for 2 years, where he pitched a total of 135 innings over 2 years, having a minimal effect on the game. Mike Leake, the Reds’ 5th starter, registered 371 innings in those 2 years.
-Baker wanted his hitters to be aggressive at the plate, which lowered their walk rate, sometimes to comical levels. Getting on base is important, and walks are a way to get on base.

I’d like to see the Reds become more cutting-edge in accepting data-driven wisdom that will improve their team’s performance. As a skilled analytics developer, its frustrating for me to see my team frequently mocked by those individuals who work full-time in baseball analytics. Maybe they’ll hire me as a consultant. I can fix them.

Maria wrote a wrap-up of the Bloomington Caravan stop for Redleg Nation. You should check it out here!

Task Switching

As a PhD student taking classes, I have a lot of tasks to switch between and focus on throughout the day. Homeworks, projects, papers to read, textbooks to read, the internet. I feel like I lose a lot of time, energy, and willpower over-thinking what I should work on next. I wonder if I should just pre-prioritize my tasks at the beginning of each day or week, and then only go the next task once the first is finished (or I am stuck without progress). It seems like it would be a big investment to start a prioritization effort like that (setup costs and commitment costs). Maybe next week…

The blog Study Hacks has multiple discussions about productivity.

Kaggle Competition to Predict March Madness

Kaggle, a site which hosts data science competitions, is hosting a new competition to predict the result of March Madness. What makes this slightly different than your standard office pool is that you predict the result of every possible match-up among the 68 teams by building a model that somehow incorporates historical data. The competition provides some standard data for past seasons and encourages competitors to supplement it with their own data. I’m interested in the results of this, but I doubt I have time to build a model of my own this semester.

Queues are a Tragedy of the Commons

Interesting job talk by Shiliang Cui today. He walked through the logic of customers joining a queue. Customers get a reward once they receive service, but have a cost that is proportional to the time spent in queue. So rational customers can join the queue or balk at the length of the line and leave. Additionally, Shiliang added the concept of retrying, where the customer leaves now but comes back later to retry at the line. Customers pay a retrial cost for this inconvenience.

By comparing the benefit from receiving service to the queue and retrial costs, optimal policies for the behavior of the customer can be found. Typically, these policies have the form: join the queue and wait for service if there are N or less customers in queue and balk or retry otherwise (depending on retrial costs).

The interesting part are the Socially Optimal Policies. If all customers were to act in a way that maximizes the benefits to society as a whole, fewer people would wait in line and more people would balk or retry. This is because, as a utility maximizing individual, I do not consider the effect on others when I decide to wait in a queue. If I did, I would wait less often, because my waiting makes the queue longer for others, which increases their queueing costs. Though Shiliang didn’t make this comparison, I feel like this is an example of The Tragedy of the Commons. When everyone considers only their own interests, their actions have negative externalities on others. The more people that join the queue, the worse off everyone is.


Thanks to Maria Schwartzman for setting up this website for me.  I hope to use this blog as a showcase for my research and research interests.  I’m a Decision Science PhD at Indiana University.  See the Projects page for an overview of my current and past projects and the About Me section for a description of my interests.  Thinking about and researching hidden aspects of sports takes a lot of my time.  If you share my sports interest and are in the Bloomington area, see the Sports Open House section.  As always, everything is under construction right now.